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Job satisfaction and turnover decision of employees in the Internet sector in the US
- Publication Year :
- 2022
-
Abstract
- This paper proposes that high value on the work-life balance, compensation, career opportunity and fitness of culture and management style would improve job satisfaction. A turnover risk prediction model based on the random forest is constructed to understand the turnover risk feature and identify risk. Using a sample of 17,724 online reviews of employees from Glassdoor, the positive effect of antecedents, the job satisfaction variable as a mediator, and the unemployment rate variable as a moderator is verified. Finally, job satisfaction is identified as the most important feature for predicting turnover based on the random forest algorithm.
Details
- Database :
- OAIster
- Notes :
- text, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1406119691
- Document Type :
- Electronic Resource